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Analysis of machine learning integration into supply chain management

Authors :
Rodríguez, Elen Yanina Aguirre
Rodríguez, Elias Carlos Aguirre
Silva, Aneirson Francisco da
Rizol, Paloma Maria Silva Rocha
Miranda, Rafael de Carvalho
Marins, Fernando Augusto Silva
Source :
International Journal of Logistics Systems and Management; 2024, Vol. 47 Issue: 3 p327-355, 29p
Publication Year :
2024

Abstract

The application of machine learning (ML) techniques in supply chain (SC) processes has been gaining popularity over the last years, because ML significantly helps making the SC faster and more efficient, automatising its processes, improving decision making, and mitigating risks, among other benefits that results in cost savings or more profits. The goal of this work was to analyse the existing studies about the integration of ML into supply chain management (SCM), exploring gaps and trends, from a bibliometric analysis of the articles published. The analysis consisted of assessing the total number of published documents between 2000 and 2020. The main contribution of this research was the identification of significant details about the studies conducted involving the integration of ML and SCM, which will help in the development of new studies in this important area.

Details

Language :
English
ISSN :
17427967 and 17427975
Volume :
47
Issue :
3
Database :
Supplemental Index
Journal :
International Journal of Logistics Systems and Management
Publication Type :
Periodical
Accession number :
ejs65576949
Full Text :
https://doi.org/10.1504/IJLSM.2024.136856